ollama_llm
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ollama_llm [2024/04/24 17:18] jpummil |
ollama_llm [2024/04/27 02:59] (current) jpummil |
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| Ollama is an open source inference engine for running LLM models. [[https:// | Ollama is an open source inference engine for running LLM models. [[https:// | ||
| - | To run a local LLM, you need two ingredients: | + | To run a local LLM, you need two ingredients: |
| - | AHPCC is making this tool available to our users in a limited fashion so as not to impact the broad array of research tasks making their way thru the queues. As such, Ollama is only available | + | AHPCC is making this tool available to our users in a limited fashion so as not to impact the broad array of research tasks making their way thru the queues. As such, Ollama is available and can be accessed |
| + | |||
| + | For a query to a model, you can do so via a login node as follows: | ||
| < | < | ||
| - | srun -p pcon06 -N1 -n1 -q comp -t 06:00:00 -C 4titanv --pty /bin/bash | + | ollama-ahpcc run < |
| </ | </ | ||
| - | Once you are logged in to your session, you need to determine which LLM model you wish to use for the session. To see the available models: | + | You need to determine which LLM model you wish to use for the query. More information about the various models can be seen here: https:// |
| + | To see the available models: | ||
| < | < | ||
| - | $ ollama list | + | $ ollama-ahpcc |
| NAME | NAME | ||
| all-minilm: | all-minilm: | ||
| Line 28: | Line 32: | ||
| </ | </ | ||
| - | There are two ways to utilize Ollama. Interactively, | + | For querying with a single command |
| - | + | ||
| - | To use a session interactively... | + | |
| < | < | ||
| - | ollama run < | + | ollama-ahpcc |
| </ | </ | ||
| - | When you are done with the session, exit with the command... | + | Here is a brief example of running a simple query with result... |
| - | + | ||
| - | < | + | |
| - | /bye> | + | |
| - | </ | + | |
| - | + | ||
| - | For querying with a single command from outside the Ollama shell... | + | |
| < | < | ||
| - | ollama run < | + | ollama-ahpcc |
| - | </ | + | |
| - | Here is a brief example of running a simple query with result... | ||
| - | |||
| - | < | ||
| - | ollama run llama3 How many states are in the USA? | ||
| There are 50 states in the United States of America (USA). | There are 50 states in the United States of America (USA). | ||
| </ | </ | ||
| Line 58: | Line 49: | ||
| < | < | ||
| - | ollama run llama3 Please list in JSON format the names, state capitols, and populations of all 50 US states | + | ollama-ahpcc |
| Here is the list of 50 US states with their names, state capitals, and populations in JSON format: | Here is the list of 50 US states with their names, state capitals, and populations in JSON format: | ||
| Line 86: | Line 77: | ||
| < | < | ||
| - | ollama run llama3 Please list all 50 US states >> states.txt | + | ollama-ahpcc |
| </ | </ | ||
| Line 92: | Line 83: | ||
| < | < | ||
| - | ollama run llama3 "$(cat nas.f90)" | + | ollama-ahpcc |
| This is a Fortran code file, specifically a main program and subroutine for solving a partial differential | This is a Fortran code file, specifically a main program and subroutine for solving a partial differential | ||
| equation (PDE) using a finite difference method. The code appears to be part of a larger numerical simulation | equation (PDE) using a finite difference method. The code appears to be part of a larger numerical simulation | ||
| Line 113: | Line 105: | ||
| </ | </ | ||
| - | As we are all still learning how to efficiently and properly utilize LLM's in our daily life, you may be better served looking on the Ollama GitHub site under " | + | Input size for Ollama is somewhat limited (perhaps 1000 lines?), so it may be necessary to pare down input using other Linux tools. For example, a protein database file with 2200 lines won't fit...but paring the data down to the first 1000 lines does... |
| < | < | ||
| + | ollama-ahpcc run llama3 " | ||
| + | |||
| + | This appears to be a PDB (Protein Data Bank) file, which contains structural information about a protein or | ||
| + | protein complex. The file is formatted in a specific way and includes information such as: | ||
| + | |||
| + | * Atom coordinates (3D positions) for each atom in the protein | ||
| + | * Atom names and types (e.g. N, CA, C, O) | ||
| + | * Chain identifiers (e.g. A, B) indicating which chain a particular residue belongs to | ||
| + | </ | ||
| + | |||
| + | It should be noted that for analyzing images and other various files, it requires a multi-modal model like llava or bakllava and results seems to be a bit mixed. | ||
| + | |||
| + | As we are all still learning how to efficiently and properly utilize LLM's in our daily life, you may be better served looking on the Ollama GitHub site under " | ||
| + | |||
| https:// | https:// | ||
| + | |||
| https:// | https:// | ||
| - | </ | + | |
ollama_llm.1713979124.txt.gz · Last modified: 2024/04/24 17:18 by jpummil
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